Do not modify input labels in density filenames (#32)

* Do not modify input labes

atlas_densities/app/mtype_densities.py

@@ -204,7 +204,7 @@ def standardize_probability_map(probability_map: "pd.DataFrame") -> "pd.DataFram
     Standardize the labels of the rows and the columns of `probability_map` and
     remove unused rows.
 
-    Output labels are all lower case.
+    Output row labels are all lower case.
     The underscore is the only delimiter used in an output label.
     The layer names refered to by output labels are:
         "layer_1," "layer_23", "layer_4", "layer_5" and "layer_6".
@@ -242,9 +242,7 @@ def standardize_column_label(col_label: str):
 
         Example: "NGC-SA" -> "ngc_sa"
         """
-        col_label = col_label.replace("-", "_")
-
-        return col_label.lower()
+        return col_label.replace("-", "_")
 
     bbp_mtypes_map = {"DLAC": "LAC", "SLAC": "SAC"}
     probability_map.rename(bbp_mtypes_map, axis="columns", inplace=True)
@@ -312,7 +310,7 @@ def create_from_probability_map(
     else:
         probability_map.set_index(probability_map.columns[0], inplace=True)
 
-    # Remove useless lines, use lower case and "standardized" explicit label names
+    # Remove useless lines, use lower case row labels and "standardized" explicit label names
     probability_map = standardize_probability_map(probability_map)
     check_probability_map_sanity(probability_map)
 

atlas_densities/densities/mtype_densities_from_map.py

@@ -60,7 +60,6 @@ def _check_dataframe_labels_sanity(dataframe: "pd.DataFrame") -> None:
         AtlasBuildingTools error on failure.
     """
     d_f = dataframe.copy()
-    d_f = d_f.rename(str.lower, axis="columns")
     d_f = d_f.rename(str.lower, axis="rows")
     d_f.columns = d_f.columns.str.replace(" ", "")
     d_f.index = d_f.index.str.replace(" ", "")
@@ -161,14 +160,14 @@ def create_from_probability_map(
 
     The ouput volumetric density for the mtype named ``mtype`` is saved into
     `<output_dirpath>/no_layers` under the name ``<mtype>_densities.nrrd`` if its sum is not too
-    close to zero where <mtype> is uppercase and dash separated.
+    close to zero, where <mtype> is dash separated.
     Example: if mtype = "ngc_sa", then output_file_name = "NGC-SA_densities.nrrd".
 
     The restriction of the volumetric density for the mtype named ``mtype`` to layer
     ``layer_name`` is saved into `<output_dirpath>/with_layers` under the name
     ``<layer_name>_<mtype>_densities.nrrd`` if its sum is not too close to zero.
     The string <layer_name> is of the form "L<layer_index>", e,g, "L1" for "layer_1" and
-    the string <mtype> is upper case and dash-separted.
+    the string <mtype> is dash-separted.
     Example: if mtype = "ngc_sa", layer_name = "layer_23",  then
     output_file_name = "L23_NGC-SA_densities.nrrd".
 
@@ -243,20 +242,18 @@ def create_from_probability_map(
         )
 
         # Saving to file
+        mtype_filename = f"{mtype.replace('_', '-')}_densities.nrrd"
         (Path(output_dirpath) / "no_layers").mkdir(exist_ok=True, parents=True)
         if not np.isclose(np.sum(mtype_density), 0.0):
-            filename = f"{mtype.upper().replace('_', '-')}_densities.nrrd"
-            filepath = str(Path(output_dirpath) / "no_layers" / filename)
+            filepath = str(Path(output_dirpath) / "no_layers" / mtype_filename)
             L.info("Saving %s ...", filepath)
             annotation.with_data(mtype_density).save_nrrd(filepath)
 
         (Path(output_dirpath) / "with_layers").mkdir(exist_ok=True, parents=True)
         for layer_name, layer_mask in layer_masks.items():
             layer_density = np.zeros(layer_mask.shape, dtype=float)
             layer_density[layer_mask] = mtype_density[layer_mask]
-            filename = (
-                f"L{layer_name.split('_')[-1]}_{mtype.upper().replace('_', '-')}_densities.nrrd"
-            )
+            filename = f"L{layer_name.split('_')[-1]}_{mtype_filename}"
             if not np.isclose(np.sum(layer_density), 0.0):
                 filepath = str(Path(output_dirpath) / "with_layers" / filename)
                 L.info("Saving %s ...", filepath)

tests/app/test_mtype_densities.py

@@ -160,10 +160,10 @@ def test_standardize_probability_map(self):
         actual = tested.standardize_probability_map(probability_map)
         expected = pd.DataFrame(
             {
-                "chc": [0.5, 0.0, 0.0, 0.0],
-                "ngc_sa": [0.5, 0.0, 0.0, 0.0],
-                "lac": [0.0] * 4,
-                "sac": [0.0] * 4,
+                "ChC": [0.5, 0.0, 0.0, 0.0],
+                "NGC_SA": [0.5, 0.0, 0.0, 0.0],
+                "LAC": [0.0] * 4,
+                "SAC": [0.0] * 4,
             },
             index=["layer_1_gad67", "layer_6_vip", "layer_23_pv", "layer_4_vip"],
         )
@@ -176,7 +176,7 @@ def test_output(self):
             result = get_result_from_probablity_map_(runner)
             assert result.exit_code == 0
 
-            chc = VoxelData.load_nrrd(str(Path("output_dir") / "no_layers" / "CHC_densities.nrrd"))
+            chc = VoxelData.load_nrrd(str(Path("output_dir") / "no_layers" / "ChC_densities.nrrd"))
             assert chc.raw.dtype == float
             npt.assert_array_equal(chc.voxel_dimensions, self.data["annotation"].voxel_dimensions)
 

tests/densities/test_mtype_densities_from_map.py

@@ -136,7 +136,7 @@ def create_from_probability_map_data():
 
     probability_map = DataFrame(
         {
-            "chc": [
+            "ChC": [
                 0.0,
                 0.0,
                 0.0,
@@ -155,7 +155,7 @@ def create_from_probability_map_data():
                 1.0,
                 1.0,
             ],
-            "lac": [
+            "LAC": [
                 1.0,
                 1.0,
                 1.0,
@@ -235,7 +235,7 @@ def test_filenames(self):
         no_layers_filepaths = {
             Path.resolve(f).name for f in Path(tmpdir, "no_layers").glob("*.nrrd")
         }
-        assert no_layers_filepaths == {"CHC_densities.nrrd", "LAC_densities.nrrd"}
+        assert no_layers_filepaths == {"ChC_densities.nrrd", "LAC_densities.nrrd"}
         with_layers_filepaths = {
             Path.resolve(f).name for f in Path(tmpdir, "with_layers").glob("*.nrrd")
         }
@@ -244,19 +244,19 @@ def test_filenames(self):
             "L4_LAC_densities.nrrd",
             "L23_LAC_densities.nrrd",
             "L6_LAC_densities.nrrd",
-            "L6_CHC_densities.nrrd",
-            "L5_CHC_densities.nrrd",
+            "L6_ChC_densities.nrrd",
+            "L5_ChC_densities.nrrd",
         }
 
     def test_output_consistency(self):
         sum_ = {
-            "CHC": np.zeros(self.data["annotation"].shape, dtype=float),
+            "ChC": np.zeros(self.data["annotation"].shape, dtype=float),
             "LAC": np.zeros(self.data["annotation"].shape, dtype=float),
         }
         tmpdir = self.tmpdir.name
-        for filename in ["L5_CHC_densities.nrrd", "L6_CHC_densities.nrrd"]:
+        for filename in ["L5_ChC_densities.nrrd", "L6_ChC_densities.nrrd"]:
             filepath = str(Path(tmpdir) / "with_layers" / filename)
-            sum_["CHC"] += VoxelData.load_nrrd(filepath).raw
+            sum_["ChC"] += VoxelData.load_nrrd(filepath).raw
 
         for filename in [
             "L1_LAC_densities.nrrd",
@@ -267,7 +267,7 @@ def test_output_consistency(self):
             filepath = str(Path(tmpdir) / "with_layers" / filename)
             sum_["LAC"] += VoxelData.load_nrrd(filepath).raw
 
-        for mtype in ["CHC", "LAC"]:
+        for mtype in ["ChC", "LAC"]:
             filepath = str(Path(tmpdir) / "no_layers" / f"{mtype}_densities.nrrd")
             density = VoxelData.load_nrrd(filepath)
             npt.assert_array_equal(
@@ -279,10 +279,10 @@ def test_output_consistency(self):
     def test_output_values(self):
         tmpdir = self.tmpdir.name
         expected_densities = {
-            "CHC": np.array([[[0.0, 0.0, 0.0, 2.0, 0.4]]], dtype=float),
+            "ChC": np.array([[[0.0, 0.0, 0.0, 2.0, 0.4]]], dtype=float),
             "LAC": np.array([[[1.5, 2.0, 1.0, 0.0, 0.6]]], dtype=float),
         }
-        for mtype in ["CHC", "LAC"]:
+        for mtype in ["ChC", "LAC"]:
             filepath = str(Path(tmpdir) / "no_layers" / f"{mtype}_densities.nrrd")
             npt.assert_array_almost_equal(
                 VoxelData.load_nrrd(filepath).raw, expected_densities[mtype]
@@ -308,17 +308,17 @@ def create_densities(self):
         )
 
     def test_probability_map_sanity_negative_probability(self):
-        self.data["probability_map"].loc["layer_1_gad67", "chc"] = -0.0025
+        self.data["probability_map"].loc["layer_1_gad67", "ChC"] = -0.0025
         with pytest.raises(AtlasDensitiesError):
             self.create_densities()
 
     def test_probability_map_sanity_row_sum_is_1(self):
-        self.data["probability_map"].loc["layer_1_gad67", "chc"] = 2.0
+        self.data["probability_map"].loc["layer_1_gad67", "ChC"] = 2.0
         with pytest.raises(AtlasDensitiesError):
             self.create_densities()
 
     def test_labels_sanity(self):
-        self.data["probability_map"].rename(str.upper, axis="columns", inplace=True)
+        self.data["probability_map"].rename(str.upper, axis="rows", inplace=True)
         with pytest.raises(AtlasDensitiesError):
             self.create_densities()